## Rows: 10886 Columns: 12
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## dbl (11): season, holiday, workingday, weather, temp, atemp, humidity, wind...
## dttm (1): datetime
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
It seems that there is no difference.
## `summarise()` has grouped output by 'season'. You can override using the
## `.groups` argument.
When temp is less than 35 Celsius, the correlation is positive. But if the temperature is too high, people don’t like to ride bikes.
## `geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'
It is clear that around 9 a.m. and 6 p.m. is the peak period for rentals, which also coincides with people’s commuting times.
It can be seen temp is positively correlated with count, humidity and weather are negatively correlated with count.